OBO Foundry dashboard analysis¶

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/tmp/ipykernel_604/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    5
Name: syntax, dtype: int64

Breakdown of used Axiom Types

count mean std min 25% 50% 75% max
AnnotationAssertion 5 101597.0 160052.701122 2.0 8675.0 10773.0 112828.0 375707.0
Declaration 5 11844.2 13661.893489 2.0 1989.0 5628.0 19437.0 32165.0
EquivalentClasses 5 3478.2 3415.438654 1.0 584.0 2842.0 6196.0 7768.0
SubAnnotationPropertyOf 3 9.4 16.334014 0.0 0.0 1.0 8.0 38.0
SubClassOf 3 13809.0 20472.859827 0.0 0.0 1167.0 21193.0 46685.0
SubPropertyChainOf 2 1.6 3.049590 0.0 0.0 0.0 1.0 7.0
DisjointClasses 1 15.6 34.882660 0.0 0.0 0.0 0.0 78.0
SubObjectPropertyOf 1 0.8 1.788854 0.0 0.0 0.0 0.0 4.0
SymmetricObjectProperty 1 0.2 0.447214 0.0 0.0 0.0 0.0 1.0

Breakdown of used OWL Class Expression constructs

count mean std min 25% 50% 75% max
Class 5 51784.6 65273.674661 3.0 6184.0 14550.0 88806.0 149380.0
ObjectSomeValuesFrom 5 8784.2 10113.238512 1.0 1151.0 3257.0 18663.0 20849.0
ObjectIntersectionOf 4 3890.2 3820.952656 0.0 717.0 2926.0 7754.0 8054.0
ObjectUnionOf 2 12.4 20.803846 0.0 0.0 0.0 14.0 48.0

OBO Score (Experimental)

ontology score score_dash score_impact
1 hp 0.560 0.800 0.4
2 maxo 0.531 0.727 0.4
0 ecto 0.458 0.844 0.2
3 mondo 0.389 0.973 0.0
4 tmp 0.113 0.282 0.0

OBO Score Summary

count mean std min 25% 50% 75% max
score 5.0 0.4102 0.178952 0.113 0.389 0.458 0.531 0.560
score_dash 5.0 0.7252 0.263412 0.282 0.727 0.800 0.844 0.973
score_impact 5.0 0.2000 0.200000 0.000 0.000 0.200 0.400 0.400

OBO dependency graph